Improving parking availability prediction in smart cities with IoT and ensemble-based model

Alkheder, 2016, Parking problems in Abu Dhabi, UAE toward an intelligent parking management system ’ADIP: Abu Dhabi Intelligent Parking’, Alexandria Eng. J., 55, 2679, 10.1016/j.aej.2016.06.012 Almeida, 2015, PKLot-A robust dataset for parking lot classification, Expert Syst. Appl., 42, 4937, 10.1016/j.eswa.2015.02.009 Amato, 2016, Car parking occupancy detection using smart camera networks and deep learning Amato, 2017, Deep learning for decentralized parking lot occupancy detection, Expert Syst. Appl., 72, 327, 10.1016/j.eswa.2016.10.055 Arasteh, 2016, Iot-based smart cities: a survey Bachani, 2016, Performance analysis of proximity and light sensors for smart parking, Proc. Comput. Sci., 83, 385, 10.1016/j.procs.2016.04.200 Bélissent, 2010 Camero, 2018, Evolutionary deep learning for car park occupancy prediction in smart cities, 386 De Fabritiis, Corrado, Ragona, Roberto, Valenti, Gaetano, 2008. Traffic estimation and prediction based on real time floating car data, Intelligent Transportation Systems. ITSC 2008. 11th International IEEE Conference on, 2008. Faris, 2019, Improving financial bankruptcy prediction in a highly imbalanced class distribution using oversampling and ensemble learning: a case from the Spanish market, Progr. Artif. Intell., 1 Freund, Y., Schapire, R.E., 1996. Experiments with a new boosting algorithm. In icml vol. 96, pp. 148–156. Freund, 1999, A short introduction to boosting, J.-Jpn. Soc. Artif. Intell., 14, 1612 Gandhi, 2016, A prototype for IoT based car parking management system for smart cities, Indian J. Sci. Technol., 9, 1 Géron, 2017 Giuffr, 2012, A novel architecture of parking management for smart cities, Procedia-Soc. Behav. Sci., 53, 16, 10.1016/j.sbspro.2012.09.856 Imandoust, 2013, Application of k-nearest neighbor (KNN) approach for predicting economic events: theoretical background, Int. J. Eng. Res. Appl., 3, 605 Jin, 2014, An information framework for creating a smart city through internet of things, IEEE Internet Things J., 1, 112, 10.1109/JIOT.2013.2296516 Khurana, 2018, Green cover change detection using a modified adaptive ensemble of extreme learning machines for North-Western India, J. King Saud Univ.-Comput. Inf. Sci. Kubler, 2016, IoT-based smart parking system for sporting event management Kumar, 2007, A comparative study of different sensors for smart car park management Lin, 2017, A survey of smart parking solutions, IEEE Trans. Intell. Transp. Syst., 3229, 10.1109/TITS.2017.2685143 Mago, 2018, A machine learning technique for detecting outdoor parking, Int. J. Eng. Technol., 7, 39, 10.14419/ijet.v7i2.30.13460 Mainetti, 2015, A Smart Parking System based on IoT protocols and emerging enabling technologies Mishra, 2017, Adaptive boosting of weak regressors for forecasting of crop production considering climatic variability: an empirical assessment, J. King Saud Univ.-Comput. Inf. Sci. Pawowicz, 2019, Infrastructure of RFID-based smart city traffic control system, 186 Pow, N., Janulewicz, E., Liu, L., 2014. Applied Machine Learning Project 4 Prediction of real estate property prices in Montréal. Rajabioun, 2015, On-street and off-street parking availability prediction using multivariate spatiotemporal models, IEEE Trans. Intell. Transp. Syst., 16, 2913, 10.1109/TITS.2015.2428705 Rodier, 2010, Transit-based smart parking: an evaluation of the San Francisco bay area field test, Transp. Res. Part C: Emerging Technol., 18, 225, 10.1016/j.trc.2009.07.002 Sharma, 2019, An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm, J. King Saud Univ.-Comput. Inf. Sci. Shoeibi, 2019, Future of smart parking: automated valet parking using deep Q-Learning, 177 Sinta, 2014, Ensemble k-nearest neighbors method to predict rice price in Indonesia, Appl. Math. Sci., 8, 7993 Stolfi, 2017, Predicting car park occupancy rates in smart cities, 107 Tang, 2005, Traffic-incident detectionalgorithm based on nonparametric regression, IEEE Trans. Intell. Transp. Syst., 6, 38, 10.1109/TITS.2004.843112 Xiang, 2017, Real-time parking occupancy detection for gas stations based on Haar-AdaBoosting and CNN, IEEE Sens. J., 17, 6360, 10.1109/JSEN.2017.2741722 Xu, 2017, Bus arrival time prediction with real-time and historic data, Cluster Comput., 20, 3099, 10.1007/s10586-017-1006-1 Yoo, 2008, PGS: Parking Guidance System based on wireless sensor network, 218 Zantalis, 2019, A review of machine learning and IoT in smart transportation, Fut. Internet, 11, 94, 10.3390/fi11040094 Zhang, 2015, A gradient boosting method to improve travel time prediction, Transp. Res. Part C: Emerging Technol., 58, 308, 10.1016/j.trc.2015.02.019 Zheng, 2015, Parking availability prediction for sensor-enabled car parks in smart cities